Responsible AI for labour market equality
BIAS is an interdisciplinary project to understand and tackle the role of AI algorithms in shaping ethnic and gender inequalities in the labour market, which is now increasingly digitized.
The project seeks to understand and minimise gender and ethnic biases in the AI-driven labour market processes of job advertising, hiring and professional networking. We further aim to develop 'responsible' AI that mitigates biases and attendant inequalities, by designing AI algorithms and development protocols that are sensitive to such biases. The empirical context of our investigation includes these labour market processes in organisations and on digital job platforms.
Our project comprises two interlinked work packages that respectively understand the different dimensions of bias from a multi-stakeholder perspective (e.g. employer, employee, digital platform developer) through in-depth data mining and qualitative investigations when AI algorithms are used in the labour market processes of job advertising, hiring and professional networking; and test/design new AI algorithms to mitigate them and create protocols for their development and implementation.
About the Project
Tab Content: Overview
Potential 'biases' produced by AI technologies may significantly undermine labour market equality and stymy equitable and sustainable socio-economic development. BIAS's objectives speak directly to multiple national priority agendas in both the UK and Canada - gender pay gap, ethnic/racial disparity, digital and industrial strategy.
As both the UK and Canada look to embrace digital transformations as part of their national (economic and industrial) strategies, our focus on the implications of such transformations for labour market equalities and our objective to reduce such inequalities through the responsible development and deployment of AI promises a broad range of impacts, which are pertinent to the future of labour relations, economic competitiveness, human resource management, and industrial strategies.
Tab Content: People
- Monideepa Tarafdar
- Bran Knowles (Data Science)
- Yang Hu (Sociology)
- Jabir Alshehabi Al-Ani
- Irina Rets
Tab Content: Publications
Publications coming soon
Tab Content: Advisory Board
Henrik Nordmark has a passion for the interplay between mathematics, psychology and philosophy and how these can be applied to have positive impact in the real world. As Head of Data Science at Profusion, he leads our team of data scientists, analysts and engineers to apply statistics and machine learning in novel ways to solve business problems. He leads R&D of data science techniques, working with our university partners to bring the cutting edge of latest thinking to the business sector, and leading our innovation projects funded by Innovate UK. Having built our own team, he now spearheads our Data Academy to train new talent to enter the profession and help our clients build their teams. His own academic background included completing two degrees simultaneously in Mathematics and Psychology with High Distinction before an MSc in Statistics & Computer Science which won the Townsend Prize for best MSc dissertation of the year. While at Profusion, he completed an Executive MBA at Hult International Business School and was named in the Data IQ 100 2018, as one the top 100 most influential data professionals in the UK.
Professor James Hendler is the Director of the Institute for Data Exploration and Applications and the Tetherless World Professor of Computer, Web and Cognitive Sciences at Rensselaer Polytechnic Institute. He also is acting director of the RPI-IBM Artificial Intelligence Research Collaboration and serves as a member of the Board of the UK’s charitable Web Science Trust. Hendler has authored over 400 books, technical papers and articles in the areas including artificial intelligence, such as "Social Machines: The Coming Collision of Artificial Intelligence, Social Networking, and Humanity" (2016). In his recent work, James is looking at representation inequality in conversational AI with respect to ethnicity and non-binary (or trans) gender issues.
Lee Gudgeon has worked in the recruitment industry for over 22 years and has held the position of Managing Director of Reed Talent Solutions (RTS) since 2016. Reed Talent Solutions delivers bespoke, outsourced recruitment contracts to both local and national organisations across the UK.
Lee has been instrumental in developing the RTS mission: to provide digital workforce solutions that deliver measurable benefits to clients and customers. To achieve this, RTS champions a culture of continuous improvement and innovation, driven by the company motto “Better Never Stops”.
Professor Randy Goebel is currently professor of Computing Science in the Department of Computing Science at the University of Alberta, Associate Vice President (Research) and Associate Vice President (Academic), and Fellow and co-founder of the Alberta Machine Intelligence Institute (AMII).
Professor Goebel's theoretical work on abduction, hypothetical reasoning and belief revision is internationally well known, and his recent research is focused on the formalization of visualization and explainable artificial intelligence (XAI).
Professor Nancy Reid is University Professor and Canada Research Chair in Statistical Methodology at the University of Toronto. Her research interests are in statistical theory, likelihood inference, and design of studies.
She is the former Director of the Canadian Statistical Sciences Institute, and has served on the scientific advisory panels of the National Program on Complex Data Structures, the Centre de Recherches Mathématiques, the Fields Institute for Research in the Mathematical Sciences, the Pacific Institute for Mathematical Sciences, and the Banff International Research Station.
Dr. Charmaine B. Dean is Vice-President, Research and International at the University of Waterloo. In this role, she is focused on building upon foundational strengths to heighten the emphasis on collaborations, and link related external portfolios in a systematic approach to industrial partners and entrepreneurship.
An engaged member of several relevant boards including, Compute Ontario, the Southern Ontario Smart Computing Innovation Platform, the Vector Institute for Artificial Intelligence and the Institute for Cybersecurity and Privacy, Dr. Dean has also served as a board member for the US National Institute of Statistical Sciences (NISS) Corporation, the National Institute for Complex Data Structures and the Canadian Statistical Sciences Institute. She is dedicated to developing outstanding computing capabilities for researchers and for building capacity in Canada and is interested in bringing together diverse communities to drive forward a unified direction for data management activities and priorities.
Jonathan Crook is Director of Balkern. He has worked in the technology industry for over ten years, with particular emphasis on Enterprise Applications implemented as Software as a Service. He has worked with companies all over the world, from Lebanon to Argentina and in industries as varied as logistics and utilities. Two of the Enterprise Applications developed were shortlisted for UK innovation awards.
Jonathan has an academic background in strategic studies and risk management, with degrees from Lancaster University, University of Leicester and Madras University, India, together with a full time MBA from Hult International Business School.
Matissa Hollister is an Assistant Professor of Organizational Behavior at the Desautels Faculty of Management at McGill University. She received a Masters of City Planning from Massachusetts Institute of Technology and a PhD in Sociology and Social Policy from Harvard University. Professor Hollister's research examines how the employer-employee relationship has changed over the past five decades in North America and other developed countries. Particular areas of focus include the rise of job instability, the move from internal to external labour markets, and the impact of technology and artificial intelligence on employment practices and outcomes. She is currently serving as the McGill University Fellow with the World Economic Forums' Centre for the Fourth Industrial Revolution.
Leah Ruppanner is an Associate Professor of Sociology and Co-Director of The Policy Lab at the University of Melbourne. Her research investigates gender and its intersection to inequalities, technologies and policies. Associate Professor Ruppanner is leading a project on gender bias in hiring algorithms to understand how gender bias limits women's access to employment in Australia and the US. This project builds upon Ruppanner's breadth of expertise on gender inequality in the home, workplace, and government. Associate Ruppanner is a leading expert on COVID-19 and its impact on gender inequality in US and Australia. Her book, Motherlands: How States Push Mothers out of Employment (2020) provides a typology of childcare and gender policies and their relationship to mothers' employment varies across US states. This has led to a range of high impact publications showing women have divergent experiences based on their state of residence. Ruppanner's research is published in Demography, Journal of Marriage and Family, Sociological Methods and Research, European Sociological Review and Social Science Research.
News and Blogs
Too many businesses failing to properly embrace AI into their processes in order to reap benefits
Businesses need to actively embrace artificial intelligence as research from Lancaster University Management School shows most business and technology leaders are optimistic about the value-creating potential of AI in their enterprise but that benefits have proved elusive for a majority of organisations.
BIAS project examines how Artificial Intelligence can lead to unintentional bias in the processes of job advertising, hiring and professional networking. Research partnership @LancasterUni @Uni_of_Essex @UAlberta, funded by @UKRI_News @SSHRC_CRSH https://t.co/isOjCsPpXr